Current Practices and Experiences Accessing Care for Mental Health Issues of Inflammatory Arthritis Patients from the Rheum4U Precision Health Registry
Bibliographic record
Abstract
Objectives To understand how patients with inflammatory arthritis (IA) currently obtain access to mental healthcare resources and identify strategies to enhance support during rheumatology clinic visits. Methods Patients and healthcare providers participated in semi-structured interviews or focus groups. Patients were recruited from the Rheum4U Precision Health Registry using purposive sampling. Healthcare providers from 2 rheumatology clinics were approached in-person or by email to participate. Prior to interviews/focus groups, participants completed a survey with closed-ended questions about mental healthcare resources. The interviews/focus groups explored the use of mental health screening questionnaires and experiences of patients accessing mental healthcare resources themselves or through healthcare providers. Cognitive task analysis,[1] and service blueprinting,[2] organized and mapped current practices. The analysis will be used to create recommended care pathways, which will be later reviewed for feedback by participants. Results Six patients and 3 rheumatologists participated in interviews. Two allied health professionals and 5 nurses participated in interviews or focus groups. Four patients reported having anxiety/depression, 4 patients indicated they never discussed their mental health at rheumatology clinic visits, and none of them were using any mental healthcare resources at the time. All healthcare providers have referred patients to mental health resources, and almost all would like to discuss their patients’ mental health. Key findings included: Patients with strong social-support networks did not require assistance from healthcare providers to access resources. Some patients preferred to get assistance at the rheumatology clinic, while others consulted their general practitioner (GP), or were unsure of where to seek help for mental health concerns. After inquiring about mental health, clinic staff would refer patients to the social worker or provide relevant information. Some rheumatologists screened patients themselves to assess needs and resources and sometimes referred them to the social worker. Commonly used resources included employment assistance programs, community resources, mental health websites, and crisis lines. Rheumatologists sometimes informed their patient’s GP about mental health concerns through summaries sent via the electronic medical record system, but follow-up communication was often lacking. Figure 1 depicts a summarized journey of how patients with IA currently receive support for mental health concerns. Conclusion Access to mental health resources for patients with IA varies significantly. Streamlining support for patients could involve allied health professionals assisting rheumatologists with screening, developing a quick reference guide with available resources, and enhancing communication between involved healthcare providers to ensure continuity of care. [1.] Clark R. Handbook of research on educational communications and technology. Springer Science & Business Media; 2014:541-55. [2.] Bitner MJ. California Management Review 2008;50(3):66-94.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".